DATFID transforms black-box AI forecasting into transparent, traceable decisions.
Born from over ten years of research in quantitative analysis, econometrics and software development, our software delivers instantly interpretable forecasts for entire portfolios, without training, tuning or GPU infrastructure.
DATFID acts as a forecasting layer that integrates seamlessly into existing systems without complex adjustments or system changes. By considering dependencies between products, locations, or other entities over time, DATFID improves the quality of results by up to 20% compared to conventional methods and reduces the overall analysis effort by more than 50%. Companies not only understand what will happen, but also why: DATFID makes cause-and-effect relationships visible, builds confidence in the results, and enables hedge fund-level predictive analytics without the need to build a PhD team.
DATFID transforms black-box AI forecasting into transparent, interpretable decisions. Built on more than ten years of research and development in quantitative analysis, econometrics, and software engineering, our software delivers instantly interpretable forecasts for entire portfolios, without training, tuning, or GPU infrastructure. DATFID acts as a forecasting layer that integrates seamlessly into existing systems, without requiring complex adaptations or system changes. By capturing dependencies between products, locations, or other entities over time, DATFID improves result quality by up to 20% compared with common methods while reducing total analysis effort by more than 50%. Companies understand not only what will happen, but also why: DATFID reveals cause-and-effect relationships, builds trust in the results, and enables predictive analytics at hedge-fund level, without the need to build a PhD team.